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SynCity: Training-Free Generation of 3D Worlds

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arxiv 2503.16420 v1 pith:WKSRT7MA submitted 2025-03-20 cs.CV

SynCity: Training-Free Generation of 3D Worlds

classification cs.CV
keywords scenessyncityworldsapproachgenerategeneratedgenerativegenerators
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We address the challenge of generating 3D worlds from textual descriptions. We propose SynCity, a training- and optimization-free approach, which leverages the geometric precision of pre-trained 3D generative models and the artistic versatility of 2D image generators to create large, high-quality 3D spaces. While most 3D generative models are object-centric and cannot generate large-scale worlds, we show how 3D and 2D generators can be combined to generate ever-expanding scenes. Through a tile-based approach, we allow fine-grained control over the layout and the appearance of scenes. The world is generated tile-by-tile, and each new tile is generated within its world-context and then fused with the scene. SynCity generates compelling and immersive scenes that are rich in detail and diversity.

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Cited by 4 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Map2World: Segment Map Conditioned Text to 3D World Generation

    cs.CV 2026-05 unverdicted novelty 6.0

    Map2World produces scale-consistent 3D worlds from text and arbitrary segment maps via a detail enhancer that incorporates global structure information.

  2. Sat2City v2: Native 3D City Asset Generation from a Single Satellite Image

    cs.CV 2026-06 unverdicted novelty 5.0

    Sat2City v2 adapts a pretrained native 3D latent model to generate controllable textured 3D city assets from satellite images via geometry flow fine-tuning and anchored texturing on a collected real dataset.

  3. Observable Performance Does Not Fully Reflect Adaptive System Organization: A Multi-Level Analysis of Gait Dynamics Under Occlusal Constraint

    cs.LG 2026-05 unverdicted novelty 4.0

    In one Parkinson's patient, six occlusal probes produce overlapping gait scores and UMAP embeddings, so observable performance does not uniquely identify adaptive system state under VDO constraint.

  4. Observable Performance Does Not Fully Reflect Adaptive System Organization: A Multi-Level Analysis of Gait Dynamics Under Occlusal Constraint

    cs.LG 2026-05 unverdicted novelty 3.0

    In a single Parkinson's patient, gait conditions with comparable linear performance metrics showed different temporal organizations in dynamical state space and unsupervised latent embeddings when vertical occlusion d...